Dynamic Prediction of Treatment Failure in Ocular Tuberculosis Using Machine Learning and Explainable AI
This study bridges basic ML research and clinical care by offering explainable, performance-driven models that support real-time, data-informed treatment decisions in managing OTB, potentially improving long-term outcomes.
Authors
- William Rojas‐Carabali (ORCID: https://orcid.org/0000-0002-9976-8989)
- Tristan Guérand
- John H. Kempen (ORCID: https://orcid.org/0000-0002-2967-4792)
- Thomas Peyrin (ORCID: https://orcid.org/0000-0002-2690-9197)
- Bernett Teck Kwong Lee (ORCID: https://orcid.org/0000-0002-2709-1972)
- Carlos Cifuentes‐González (ORCID: https://orcid.org/0000-0002-2703-0977)
- Vishali Gupta
- Justine R. Smith (ORCID: https://orcid.org/0000-0002-4756-5493)
- Germán Mejía‐Salgado (ORCID: https://orcid.org/0000-0002-1241-0715)
- Alejandra de‐la‐Torre (ORCID: https://orcid.org/0000-0003-0684-1989)
- Palvannan Rk
- John Abisheganaden
- Yap Chun Wei
- Carlos Pavesio
- Quan Dong Nguyen
- Rupesh Agrawal
Institutions
- Agency for Science, Technology and Research (SG)
- Massachusetts Eye and Ear Infirmary (US)
- Moorfields Eye Hospital NHS Foundation Trust (GB)
- National University of Singapore (SG)
- Flinders University (AU)
- Nanyang Technological University (SG)
- Singapore Immunology Network (SG)
- Tan Tock Seng Hospital (SG)
- Khoo Teck Puat Hospital (SG)
- National Institute for Health and Care Research (GB)
- Queensland Eye Institute (AU)
- Bellevue Hospital Center (US)
- Singapore Eye Research Institute (SG)
- Duke-NUS Medical School (SG)
- Moorfields Eye Hospital (GB)
- University College London (GB)
- Post Graduate Institute of Medical Education and Research (IN)
- Addis Ababa University (ET)
- Smith-Kettlewell Eye Research Institute (US)
- Universidad del Rosario (CO)
- Stanford University (US)
Publication Details
- Journal
- Translational Vision Science & Technology
- Published
- 2025-10-24
- DOI
- https://doi.org/10.1167/tvst.14.10.31
- Primary Topic
- Explainable Artificial Intelligence (XAI)
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Nanomaterials Microdevices Research Center, Osaka Institute of Technology
- Medical Research Council
- National Medical Research Council